Safety and efficacy of direct oral anticoagulation in patients with and without radiofrequency ablation of non-valvular atrial fibrillation: a multicenter retrospective cohort study.

BACKGROUND: Based on the few available studies on the prognostic benefit of using direct oral anticoagulants (DOACs) after atrial fibrillation (AF) ablation. Therefore, this study aimed to evaluate the prognostic differences between patients who underwent radiofrequency ablation (RFA) and those without RFA taking DOACs. METHODS: This is a multicenter retrospective cohort study enrolling 6137 patients with non-valvular AF (NVAF) at 15 hospitals in China. Patient information was collected through a mean follow-up of 10 months and medical record queries. Clinical outcomes included major bleeding, total bleeding, thrombosis, all-cause death, and a composite endpoint of bleeding, thrombosis, and all-cause death. RESULTS: After adjusting for confounders and propensity score matching (PSM), patients with RFA of NVAF had a significantly lower risk of major bleeding [OR 0.278 (95% CI, 0.150-0.515), P<0.001], thrombosis [OR 0.535 (95% CI, 0.316-0.908), P=0.020] and the composite endpoint [ OR 0.835 (95% CI, 0.710-0.982), P=0.029]. In the RFA PSM cohort, dabigatran was associated with reduced all-cause death in patients with RFA of NVAF [OR 0.420 (95% CI, 0.212-0.831), P=0.010]. In the no RFA PSM cohort, rivaroxaban was associated with a reduction in major bleeding [OR 0.521 (95% CI, 0.403-0.673), P<0.001], total bleeding [OR 0.114 (95% CI, 0.049-0.266), P<0.001], and the composite endpoint [OR 0.659 ( 95% CI, 0.535-0.811), P<0.001]. CONCLUSION: Among patients with NVAF treated with DOACs, RFA was a negative correlate of major bleeding, thrombosis, and composite endpoints but was not associated with total bleeding or all-cause mortality.

Association between Body Mass Index and Clinical Outcomes in Patients with Non-valvular Atrial Fibrillation Receiving Direct Oral Anticoagulants: A New Piece of Evidence on the Obesity Paradox from China.

PURPOSE: We conducted a multicenter real-world study in China to assess the association between body mass index (BMI) and clinical outcomes in patients with atrial fibrillation (AF) taking direct oral anticoagulants (DOACs). METHOD: This is a retrospective multicenter cohort study conducted in 15 centers in China. We collected demographic information through the hospital information system and obtained clinical events through follow-up visits to patients or relatives. Clinical outcomes include major, minor, total bleeding, thromboembolism, and all-cause death. RESULT: A total of 6164 patients with non-valvular AF (NVAF) were included in this study. The incidence of major bleeding in patients with NVAF differed significantly by BMI category (P < 0.001), with 5.2% in the underweight group, 2.6% in the normal group, 1.4% in the overweight group, 1.1% in the obese I group, and 1.3% in the obese II group. There was no significant difference in minor, total bleeding, and thrombosis in the five groups (P = 0.493; P = 0.172; P = 0.663). All-cause death was significantly different among the five groups (P < 0.001), with 8.9% in the underweight group, 6.3% in the normal group, 4.8% in the overweight group, 2.2% in the obese I group, and 0.4% in the obese II group. High BMI was negatively associated with major bleeding (OR = 0.353, 95% CI 0.205-0.608), total bleeding (OR = 0.664, 95% CI 0.445-0.991), and all-cause death (OR = 0.370, 95% CI 0.260-0.527). CONCLUSION: In patients with NVAF treated with DOACs, higher BMI was associated with lower major bleeding and better survival. BMI was a negative correlate of total bleeding, but not minor bleeding and thrombosis.

Effectiveness of cascading time series models based on meteorological factors in improving health risk prediction.

Meteorological factors, which are periodic and regular in a long run, have an unignorable impact on human health. Accurate health risk prediction based on meteorological factors is essential for optimal allocation of resource in healthcare units. However, due to the non-stationary and non-linear nature of the original hospitalization sequence, traditional methods are less robust in predicting it. This study aims to investigate hospital admission prediction models using time series pre-processing algorithms and deep learning approach based on meteorological factors. Using the electronic medical record data from Panyu Central Hospital and meteorological data of Panyu district from 2003 to 2019, 46,089 eligible patients with lower respiratory tract infections (LRTIs) and four meteorological factors were identified to build and evaluate the prediction models. A novel hybrid model, Cascade GAM-CEEMDAN-LSTM Model (CGCLM), was established in combination with generalized additive model (GAM), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and long-short term memory (LSTM) networks for predicting daily admissions of patients with LRTIs. The experimental results show that CGCLM multistep method proposed in this paper outperforms single LSTM model in the prediction of health risk time series at different time window sizes. Moreover, our results also indicate that CGCLM has the best prediction performance when the time window is set to 61 days (RMSE = 1.12, MAE = 0.87, R2 = 0.93). Adequate extraction of exposure-response relationships between meteorological factors and diseases and suitable handling of sequence pre-processing have an important role in time series prediction. This hybrid climate-based model for predicting LRTIs disease can also be extended to time series prediction of other epidemic disease.

The effect of nitrogen dioxide and atmospheric pressure on hospitalization risk for chronic obstructive pulmonary disease in Guangzhou, China.

BACKGROUND: The relationship between air pollution and meteorological factors on diseases has become a research hotspot recently. Nevertheless, few studies have touched the inferences of nitrogen dioxide (NO2) and atmospheric pressure (AP) on hospitalization risk for chronic obstructive pulmonary disease (COPD). OBJECTIVES: To investigate the short-term impact of particulate air pollutants and meteorology factors on hospitalizations for COPD and quantify the corresponding risk burden of hospital admission. METHODS: In our study, COPD cases were collected from Guangzhou Panyu Central Hospital (n = 11,979) from Dec of 2013 to Jun 2019. The 24-h average temperature, relative humidity (RH), wind speed (V), AP and other meteorological data were obtained from Guangzhou Meteorological Bureau. Air pollution data were collected from Guangzhou Air Monitoring Station. The influence of different NO2 and AP values on COPD risk was quantified by a distributed lag nonlinear model (DLNM) combined with Poisson Regression and Time Series analysis. RESULTS: We found that NO2 had a non-linear relationship with the incidence of COPD, with an approximate "M" type, appearing at the peaks of 126 µg/m³ (RR = 1.32, 95%CI, 1.07 to 1.64) and 168 µg/m³ (RR = 1.21, 95%CI, 0.94 to 1.55), respectively. And the association between AP and COPD incidence exhibited an approximate J-shape with a peak occurring at 1035 hPa (RR = 1.16, 95% CI, 1.02 to 1.31). CONCLUSIONS: The nonlinear relationship of NO2 and AP on COPD admission risk in different periods of lag can be used to establish an early warning system for diseases and reduce the possible outbreaks and burdens of COPD in a sensitive population.

[The expression of macrophage migration inhibition factor in pulmonary tissues of smokers with or without chronic obstructive pulmonary disease].

OBJECTIVE: To investigate the expression of macrophage migration inhibition factor (MIF) in pulmonary tissues of the smokers with and without chronic obstructive pulmonary disease (COPD). METHODS: The subjects were assigned into three groups: non-smokers without COPD (control group, n = 12), smokers without COPD (smoker group, n = 13) and smokers with COPD (COPD group, n = 16). The specimens were obtained from lung tissues as far away from cancer focus as possible (> 5 cm). Real-time quantitative PCR and immunohistochemistry were used to investigate the expression and distribution of MIF in pulmonary tissues. The relationship between the severity of airflow obstruction and the differential expressions of MIF in lung tissues of the smokers with or without COPD was analyzed. RESULTS: (1) MIF mRNA expression in COPD group (4.87 ± 1.79) was higher than that in the smoker group (2.16 ± 0.72; P < 0.01), which was higher than that in the control group (1.09 ± 0.48; P < 0.01). (2) Immunohistochemistry analysis showed that MIF protein expression in lung tissues of the COPD group (0.277 ± 0.025) was higher than that in the smokers group (0.199 ± 0.034; P < 0.01), which was significantly higher than that in control group (0.130 ± 0.021; P < 0.01). (3) Correlation analysis of MIF mRNA expression in the lung tissues and pulmonary function parameters of forced expired volume in one second (FEV(1)) percentage of predicted (FEV(1) pred)and ratio of FEV(1) to forced vital capacity (FEV(1)/FVC) suggested that MIF mRNA expression in the lung tissues was negatively related with FEV(1) pred (r = -0.578, P < 0.01) and FEV(1)/FVC (r = -0.607, P < 0.01). CONCLUSIONS: MIF expression significantly increases in the smokers with COPD, and MIF level in the lung is positively correlated with airflow limitation. The results suggest that MIF may play an important role in the pathogenesis of smoking-induced COPD.

Cumulated Ca2⁺ spike duration underlies Ca2⁺ oscillation frequency-regulated NFκB transcriptional activity.

[Ca(2+)](i) oscillations drive downstream events, like transcription, in a frequency-dependent manner. Why [Ca(2+)](i) oscillation frequency regulates transcription has not been clearly revealed. A variation in [Ca(2+)](i) oscillation frequency apparently leads to a variation in the time duration of cumulated [Ca(2+)](i) elevations or cumulated [Ca(2+)](i) spike duration. By manipulating [Ca(2+)](i) spike duration, we generated a series of [Ca(2+)](i) oscillations with the same frequency but different cumulated [Ca(2+)](i) spike durations, as well as [Ca(2+)](i) oscillations with the different frequencies but the same cumulated [Ca(2+)](i) spike duration. Molecular assays demonstrated that, when generated in 'artificial' models alone, under physiologically simulated conditions or repetitive pulses of agonist exposure, [Ca(2+)](i) oscillation regulates NFκB transcriptional activity, phosphorylation of IκBα and Ca(2+)-dependent gene expression all in a way actually dependent on cumulated [Ca(2+)](i) spike duration whether or not frequency varies. This study underlines that [Ca(2+)](i) oscillation frequency regulates NFκB transcriptional activity through cumulated [Ca(2+)](i) spike-duration-mediated IκBα phosphorylation.